Методика исполнения пейзажа на пленэре
Bibliographic record
Abstract
Список використаних джерел 1. Николай Крымов и его уроки живописи [Електронний ресурс]. – Режим доступу : http://to-priz.livejournal. com/124332.html. 2. Петько Л. В. «Невизначеність якості» з огляду на модернізацію системи освіти в Україні / Л. В. Петько // Директор школи, ліцею, гімназії : всеукр. наук.-практ. журнал / засн. МОН молодь спорту України, НАПН України, НПУ імені М. П. Драгоманова ; голов. ред. О. І. Виговська. – 2012. – № 3. – С. 56–62. 3. Рындин А. С. Живопись. Теория и практика / А.С. Рындин. – Одесса : КП ОГТ, 2010. – 287 с. 4. Хворостов, А. С. Практические упражнения на пленэре как эффективное средство эстетического воспитания учащихся [Електронний ресурс] / А. С. Хворостов // Ученые записки орловского государственного университета. Серия : гуманитарные и социальные науки. – 2012. – Вип. 4. – С. 408–411. – Режим доступу : https://elibrary.ru/item.asp?id=18211970. 5. Шевнюк О. Методика навчання образотворчого мистецтва у вищих навчальних закладах : навч. посіб. / О. Л. Шевнюк. – К, Освіта України, 2017. – 312 с. 6. Pet‟ko L. V. Brainstorming and the formation of professionally oriented foreign language teaching environment in the conditions of university (for the specialties 023 «Fine Arts» and 022 «Design») // Economics, management, law : сhallenges and рrospects: Collection of scientific articles. Psychology. Pedagogy and Education. – Discovery Publishing House Pvt. Ltd., New Delhi, India. 2016. – P. 214–217. 7. Pet‟ko L. V. Formation of professionally oriented foreign language teaching environment in the conditions of university for students of specialties 023 «Fine Arts» and 022 «Design» / L. V. Pet‟ko // Economics, management, law:realities and perspectives: Collection of scientific articles. Psychology. Pedagogy and Education. – Les Editions L'Originаlе, Paris, France. 2016. – P. 466–470. 8. Sova Olga. The essence and content of artistic-pedagogical skills in future teachers of Fine arts / Olga Sova // Intellectual Archive. – Toronto : Shiny Word.Corp. (Canada). – 2017. – November/December.– Vol. 6. – No. 6. – P. 84–92. 9. Sova O. S. The structural components of artistic-pedagogical skills for future Fine arts teachers / Olga Sova // Science and society : Collection of scientific articles. – Edizioni Magi, Roma, Italia, 2017. – P. 441–447. Shevniuk О. Axiological Approach in Professional Preparation of Future Teachers of Fine Arts // Cultura – Sztuka – Edukacja. – Tom 1. – Krakow : Wydawnictwo naukowe universytetu pedagogicznego, 2015. – P. 374–381. 10. Shevniuk O. Specific Methods of Teaching Fine Arts in Higher Educational Institutions / Olena Shevniuk // Pedagogika Przedszkolna i Wczesnoszkolna. – Vol. 3. – No.1 (5). 2015. – Krakow: Wydawnictwo naukowe un-tu pedagogicznego, 2015. – P. 7–14. 11. Ternopilska V. I. Theoretical aspects of the phenomenon – aesthetic sense // Perspective directions of scientific researches: Collection of scientific articles. – Agenda Publishing House, Coventry, United Kingdom, 2016. – P. 339–344.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.127 | 0.052 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".